After the stock market, it's the bond market's turn: UBS updates its AI "kill list," with $120 billion in corporate loans facing default risk.

When Wall Street is still trembling in fear as software stocks plummet, UBS Group has sounded a new alarm: the credit market may be the "invisible powder keg" in the AI disruption wave that has not been fully priced in. With the pace of AI technology iteration far exceeding expectations, those highly leveraged software and data service companies - especially those owned by private equity - are standing on the edge of default. Matthew Mish, Head of Credit Strategy at UBS, said in a research report released on Wednesday (December 12) that the market is repricing for a "rapid and aggressive disruption". He expects that by the end of next year, there could be an additional $75 billion to $120 billion in defaults in the leveraged loan and private credit markets alone. This estimate is based on UBS's base case scenario: a 2.5 percentage point increase in the default rate for leveraged loans, with a scale of around $1.5 trillion; a 4 percentage point increase in the default rate for private credit, with a scale of around $2 trillion. "The market reaction has been slow because they really didn't think it would happen so quickly," Mish said in an interview with CNBC. He pointed out that as companies like Anthropic and OpenAI release their latest models, the market's expectations for the timeline of AI disruption have been drastically compressed. "People have to re-adjust the way they assess the interruption risk of these loans, because this is not a problem for 2027 or 2028." From "growth story" to "fight for survival" This month, investors' narrative logic for AI has undergone a fundamental shift: the market no longer sees this technology as a universal boon for all tech companies, but rather as a ruthless reshuffle where the winners take all. While software stocks have been hit hard, the panic has quickly spilled over into seemingly unrelated industries such as finance, real estate, and trucking. Mish emphasized that under the impact of AI, companies can be clearly divided into three tiers: Tier 1: Creators of foundational large models like Anthropic and OpenAI. They are currently startups, but are highly likely to quickly rise to become the next generation of large publicly traded companies. Tier 2: Investment-grade software companies like Salesforce and Adobe. They have strong balance sheets and ample cash flow, able to defend against challengers by rapidly deploying AI. Tier 3: Software and data service companies owned by private equity. These companies generally have high levels of debt and are highly dependent on traditional business models, making them the weakest in terms of defense against AI disruption. Tail risk: What if the credit market "freezes"? In addition to the base scenario, UBS also outlined a more painful "tail risk" scenario. In this scenario, default rates would reach twice the estimated baseline, and financing channels for many companies would be cut off. "The chain reaction will be credit market tightening," Mish described, "You will have a broad repricing of leveraged credit, and credit will have an impact on the system." This scenario is similar to the junk bond sell-off of ten years ago or the credit freeze when the dot-com bubble burst over twenty years ago. UBS analysts pointed out that although risks are accumulating, the actual evolution path still depends on several key variables: the pace at which large companies adopt AI, the speed at which AI models themselves improve, and the market's refinancing needs. Currently, around 20% of leveraged loans and private credit face refinancing pressure in 2028, which means the risk will continue to ferment over the next two years. "We are not yet calling for a tail risk scenario, but we are moving in that direction," Mish admitted. Who will foot the bill for the AI revolution? It is worth noting that the leveraged loans and private credit that this warning focuses on are the riskiest sectors in the corporate credit market. They typically provide financing for companies below investment grade, many of which are supported by private equity and carry high leverage. As AI tools begin to erode the business model of traditional Software-as-a-Service (SaaS), the cash flow of these highly leveraged companies is facing unprecedented pressure. The market is concerned that if these companies fail to pivot in a timely manner during technological iterations, they will be the first "sacrifices" of this technological revolution, and ultimately, the ones holding the huge debt will foot the bill.